'commit'

DouYin/transcribe_videos.py

@@ -3,7 +3,6 @@ import os
 import asyncio
 import logging
 import sys
-from dashscope import Files
 
 # Ensure project root is in path
 sys.path.append(r"d:\dsWork\aiData")
@@ -32,104 +31,33 @@ async def transcribe_all():
         txt_path = os.path.join(transcript_dir, txt_filename)
         
         if os.path.exists(txt_path):
-            logger.info(f"Skipping (already exists): {txt_filename}")
-            continue
+            # Check if file is empty
+            if os.path.getsize(txt_path) > 0:
+                logger.info(f"Skipping (already exists): {txt_filename}")
+                continue
+            else:
+                logger.info(f"Re-processing empty file: {txt_filename}")
             
         logger.info(f"Processing: {filename}")
         
-        uploaded_file = None
         try:
-            # 1. Upload file to DashScope
-            logger.info(f"Uploading {filename} to DashScope...")
-            # Use purpose='assistants' to bypass jsonl check
-            upload_resp = Files.upload(audio_path, purpose='assistants', description=filename)
+            # Direct local file transcription using Recognition API
+            text = await client.transcribe_file(audio_path)
             
-            if upload_resp.status_code == 200:
-                # Handle output structure (dict or object)
-                output_data = upload_resp.output
-                uploaded_files = None
-                
-                if hasattr(output_data, 'uploaded_files'):
-                    uploaded_files = output_data.uploaded_files
-                elif isinstance(output_data, dict):
-                    uploaded_files = output_data.get('uploaded_files')
-                
-                if not uploaded_files:
-                     logger.error(f"No uploaded_files in response: {output_data}")
-                     continue
-
-                uploaded_file = uploaded_files[0]
-                logger.info(f"Uploaded file info: {uploaded_file}")
-                
-                # Handle uploaded_file structure
-                file_id = None
-                if hasattr(uploaded_file, 'file_id'):
-                    file_id = uploaded_file.file_id
-                elif isinstance(uploaded_file, dict):
-                    file_id = uploaded_file.get('file_id')
-                
-                if not file_id:
-                    logger.error(f"No file_id in uploaded file: {uploaded_file}")
-                    continue
-
-                logger.info(f"Uploaded successfully. File ID: {file_id}")
-                
-                # Try passing file_id. If that fails, we might need another approach.
-                # According to some docs, file_urls=["file-xxx"] works.
-                target_url = file_id 
+            if text:
+                with open(txt_path, 'w', encoding='utf-8') as f:
+                    f.write(text)
+                logger.info(f"Saved transcript to: {txt_filename}")
             else:
-                logger.error(f"Upload failed: {upload_resp}")
-                continue
-                
-            # 2. Transcribe
-            logger.info(f"Transcribing {file_id}...")
-            output = await client.transcribe_audio(file_urls=[target_url])
-            
-            if output and output.task_status == 'SUCCEEDED':
-                # Parse results
-                results = output.results
-                if results:
-                    for res in results:
-                        transcription_url = res.get('transcription_url')
-                        if transcription_url:
-                            # Download result
-                            trans_data = await client.download_transcription_result(transcription_url)
-                            if trans_data:
-                                # Extract text
-                                # text_with_ts = await client.extract_transcript_with_timestamp(trans_data)
-                                text_clean = await client.extract_transcript_without_timestamp(trans_data)
-                                
-                                # Save to file
-                                with open(txt_path, 'w', encoding='utf-8') as f:
-                                    f.write(text_clean)
-                                logger.info(f"Saved transcript to: {txt_filename}")
-                            else:
-                                logger.error(f"Failed to download transcript for {filename}")
-                        else:
-                            logger.error(f"No transcription_url in result for {filename}")
-                else:
-                    logger.error(f"No results in output for {filename}")
-            else:
-                logger.error(f"Transcription failed for {filename}")
+                logger.error(f"Failed to transcribe: {filename}")
                 
         except Exception as e:
-            logger.error(f"Error processing {filename}: {e}")
-        
-        finally:
-            # 3. Cleanup: Delete uploaded file
-            if uploaded_file:
-                try:
-                    fid = None
-                    if hasattr(uploaded_file, 'file_id'):
-                        fid = uploaded_file.file_id
-                    elif isinstance(uploaded_file, dict):
-                        fid = uploaded_file.get('file_id')
-                    
-                    if fid:
-                        Files.delete(fid)
-                        logger.info(f"Deleted remote file {fid}")
-                except Exception as e:
-                    logger.warning(f"Failed to delete remote file: {e}")
+            logger.error(f"Error processing {filename}: {str(e)}", exc_info=True)
 
 if __name__ == "__main__":
-    asyncio.run(transcribe_all())
+    try:
+        asyncio.run(transcribe_all())
+    except KeyboardInterrupt:
+        logger.info("Stopped by user")
+    except Exception as e:
+        logger.error(f"Fatal error: {str(e)}", exc_info=True)